In recent years, the popularity of “camera phones ” has increased exponentially. A larger and larger percentage of mobile telephones are being built with a camera module, which enables users to quickly and easily take digital photographs and transmit them to other devices and users.
In one typical camera phone, the phone includes a camera module 110 depicted in FIG. 1. The camera module 110 can be a stand-alone device or can be incorporated into another electronic device, such as a portable telephone. The camera module 110 includes a housing 111 which contains at least one lens 112, a primary memory unit 114, a camera processor 116, and at least one image sensor 118. The primary memory unit 114 can be used to store digital images and computer software for performing various functions in the camera module 110, as well as to implement the present invention. A removable, secondary memory unit 120 in the form of a memory card can also be included in the digital camera to provide extra memory space. The at least one image sensor 118 can be a charge coupled device (CCD), a complementary metal oxide semiconductor (CMOS), or another system. The camera module 110 may also include at least one motion sensor 130 operatively connected to the camera processor 116. When a picture of an object 128 is taken, the at least one lens 112 focuses the image onto the at least one image sensor 118 which records light electronically. The camera processor 116 then breaks this electronic information down into digital data which can be stored on the primary memory unit 114 and/or the secondary memory unit 120.
As camera-telephone combinations have become more common, users' expectations of the quality of pictures taken with the devices have also risen. Users are often no longer satisfied with digital images of a quality which was considered acceptable only a few years ago. As a result of these increased expectations, manufacturers must pay more attention to the quality of the images that are produced by their camera-phones.
There are several technical parameters that are used to describe different aspects of image quality in an image. For one, systems often monitor and measure the sharpness of an image produced by a camera. The sharpness may vary in different parts of the image, and the center area of an image is typically sharper than corner areas. Still further, systems monitor the amount of noise that is present in an image. For instance, smoothly colored areas sometimes will not be smooth, instead possessing a certain degree of graininess or noise. Systems also monitor whether the colors in the captured image are correct.
Systems also monitor whether geometric shapes in an image are distorted. Distortion can be defined as the departure of the image geometry formed by a real imaging system from that of ideal perspective projection. Distortion has the effect of shifting image points from their ideal locations, but it does not induce blurring to the image. In general, distortion is position dependent over the image area and has a vectorial character, i.e. image points are shifted both in radial and tangential directions. With distortion, straight lines may become curved in some situations.
It is often important to perform many separate measurements of the various image quality parameters. For example, a set of sample camera modules could each be measured under different operating conditions. In such a situation, it is important to have a measurement setup that yields the parameters of interest quickly and conveniently in order to maintain a low cost for performing the measurements.
Currently, technical image quality parameters are often measured so that there is a different test setup for each parameter. Some measurements are test chart-based, while others use special instruments to perform the measurements. In addition, tests have to be performed under many different conditions, such as under different camera settings, different camera-to-subject distances, and different field of views (i.e., different zoom settings or cameras with different focal lengths). Performing these measurements can become extremely expensive if several different test setups are required. Typically, even with chart-based measurements, if the field of view is changed, test charts of different sizes are required.
There are several standards that describe how a single technical parameter can be measured. Some examples include the ISO 12233: MTF measurement standard (also referred to as the spatial frequency response); the ISO 9039: Optics and optical instruments standard, which pertains to a quality evaluation of optical systems and the determination of distortion; and the ISO 15739: Photography standard, which relates to electronic still-picture imaging and noise measurements. Another system uses a rectangular checker board pattern to calibrate the cameras and/or camera modules. Such a system is described in Shu, C., Brunton, A., Fiala, M., “Automatic Grid Finding In Calibration Patterns Using Delaunay Triangulation, ” National Research Council of Canada report NRC-46497/ERB-1104, 2003.